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jerrelblankenship

Kibana MCP Server

get_dashboard

Retrieve detailed information about a specific Kibana dashboard by providing its ID to access configuration, visualizations, and data insights.

Instructions

Get detailed information about a specific dashboard

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesDashboard ID

Implementation Reference

  • The actual API client method that fetches a dashboard by ID from Kibana.
    async getDashboard(id: string): Promise<KibanaDashboard> {
      const response = await this.axiosInstance.get(
        `/api/saved_objects/dashboard/${id}`
      );
      return response.data;
    }
  • The MCP tool handler that invokes the Kibana client to retrieve a dashboard.
    case 'get_dashboard': {
      const { id } = args as { id: string };
      const dashboard = await kibanaClient.getDashboard(id);
    
      return {
        content: [
          {
            type: 'text' as const,
            text: JSON.stringify(dashboard, null, 2),
          },
        ],
      };
    }
  • The MCP tool definition and schema for the 'get_dashboard' tool.
    {
      name: 'get_dashboard',
      description: 'Get detailed information about a specific dashboard',
      inputSchema: {
        type: 'object',
        properties: {
          id: {
            type: 'string',
            description: 'Dashboard ID',
          },
        },
        required: ['id'],
      },
    },
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed information,' which implies a read-only operation, but doesn't specify what 'detailed' includes, whether it requires authentication, potential rate limits, or error handling. This is a significant gap for a tool with no structured safety hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states the tool's function without any unnecessary words. It is front-loaded with the core purpose, making it efficient and easy to parse, which is ideal for an AI agent selecting tools.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'detailed information' includes in the return value, nor does it cover behavioral aspects like permissions or errors. Given the complexity of retrieving dashboard data, more context is needed to guide the agent effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'id' parameter documented as 'Dashboard ID.' The description adds no additional semantic context beyond this, such as format examples or where to obtain the ID. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('detailed information about a specific dashboard'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_dashboards' or 'get_visualization', which would require mentioning it retrieves a single dashboard by ID rather than listing multiple or fetching visualization data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention that 'list_dashboards' should be used for listing multiple dashboards or that 'get_visualization' is for visualization-specific data, nor does it specify prerequisites like needing a dashboard ID. This leaves the agent to infer usage from context alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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